{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "72d8496c-8ab2-4231-988c-2fc12e97eb8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1994beb9-d75d-46e5-9e57-680294d34e96",
   "metadata": {},
   "outputs": [],
   "source": [
    "train=pd.read_csv('train.csv')\n",
    "test=pd.read_csv('test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e97469b4-fa52-4fea-bca3-a2c484415d3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "% of women who survived: 0.7420382165605095\n"
     ]
    }
   ],
   "source": [
    "# 取出表格中的两列，性别和存活率构建一个新的数据集women\n",
    "women = train.loc[train.Sex == 'female'][\"Survived\"]\n",
    "\n",
    "# 一共有314条女性记录，由于存活的情况是1，所以累加所有存活特征，就能得到存活数量\n",
    "# 再用存活数量/女性总数得到女性存活率\n",
    "\n",
    "rate_women = sum(women)/len(women)\n",
    "print(\"% of women who survived:\", rate_women)\n",
    "# 获得女性的存活率\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c12a849a-f440-45ab-bd01-b54e31ad647c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 12 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   PassengerId  891 non-null    int64  \n",
      " 1   Survived     891 non-null    int64  \n",
      " 2   Pclass       891 non-null    int64  \n",
      " 3   Name         891 non-null    object \n",
      " 4   Sex          891 non-null    object \n",
      " 5   Age          714 non-null    float64\n",
      " 6   SibSp        891 non-null    int64  \n",
      " 7   Parch        891 non-null    int64  \n",
      " 8   Ticket       891 non-null    object \n",
      " 9   Fare         891 non-null    float64\n",
      " 10  Cabin        204 non-null    object \n",
      " 11  Embarked     889 non-null    object \n",
      "dtypes: float64(2), int64(5), object(5)\n",
      "memory usage: 83.7+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(train.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2b4e6513-ea44-457f-97e3-8a4c3ca21010",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
      "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
      "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
      "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
      "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
      "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
      "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
      "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
      "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
      "\n",
      "            Parch        Fare  \n",
      "count  891.000000  891.000000  \n",
      "mean     0.381594   32.204208  \n",
      "std      0.806057   49.693429  \n",
      "min      0.000000    0.000000  \n",
      "25%      0.000000    7.910400  \n",
      "50%      0.000000   14.454200  \n",
      "75%      0.000000   31.000000  \n",
      "max      6.000000  512.329200  \n"
     ]
    }
   ],
   "source": [
    "print(train.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "7145aa02-a3b4-409f-854b-1f4e9de55dd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 设置中文显示问题\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus']=False  # 用来正常显示负号\n",
    "fig = plt.figure()\n",
    "fig.set(alpha = 0.5)\n",
    "# 在一张大图里分列几个小图\n",
    "plt.subplot2grid((2,3),(0,0))\n",
    "train.Survived.value_counts().plot(kind = 'bar') # 柱状图\n",
    "plt.title(\"1为获救\")\n",
    "plt.ylabel('人数')\n",
    "# 一共活了三百多个，死了五百多个\n",
    "plt.subplot2grid((2,3),(0,1))\n",
    "train.Pclass.value_counts().plot(kind=\"bar\")\n",
    "plt.ylabel(\"人数\")\n",
    "plt.title(\"乘客等级分布\")\n",
    "# 三等仓位快500，二等仓位200 ，三等舱为210\n",
    "plt.subplot2grid((2,3),(1,0), colspan=2)\n",
    "train.Age[train.Pclass == 1].plot(kind='kde')\n",
    "train.Age[train.Pclass == 2].plot(kind='kde')\n",
    "train.Age[train.Pclass == 3].plot(kind='kde')\n",
    "plt.xlabel(u\"年龄\")# plots an axis lable\n",
    "plt.ylabel(u\"密度\")\n",
    "plt.title(u\"各等级的乘客年龄分布\")\n",
    "plt.legend((u'头等舱', u'2等舱',u'3等舱'),loc='best') # sets our legend for our graph.\n",
    "\n",
    "# 统计三个港口的上岸人数\n",
    "plt.subplot2grid((2,3),(1,2))\n",
    "train.Embarked.value_counts().plot(kind='bar')\n",
    "plt.title(u\"各登船口岸上船人数\")\n",
    "plt.ylabel(u\"人数\")\n",
    "\n",
    "Survived_0 = train.Pclass[train.Survived == 0].value_counts()\n",
    "Survived_1 = train.Pclass[train.Survived == 1].value_counts()\n",
    "df=pd.DataFrame({u'获救':Survived_1, u'未获救':Survived_0})\n",
    "df.plot(kind='bar', stacked=True)\n",
    "plt.title(u\"各乘客等级的获救情况\")\n",
    "plt.xlabel(u\"乘客等级\")\n",
    "plt.ylabel(u\"人数\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a4dd8502-64b6-4e4d-8682-5e71250c2671",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "y = train[\"Survived\"]\n",
    "\n",
    "features = [\"Pclass\", \"Sex\", \"SibSp\", \"Parch\"]\n",
    "X = pd.get_dummies(train[features])\n",
    "X_test = pd.get_dummies(test[features])\n",
    "\n",
    "model = RandomForestClassifier(n_estimators=100, max_depth=5, random_state=1)\n",
    "model.fit(X, y)\n",
    "predictions = model.predict(X_test)\n",
    "\n",
    "output = pd.DataFrame({'PassengerId': test.PassengerId, 'Survived': predictions})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "028ccf19-66d8-4b13-9788-fbfc426481a1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
